Transcriptional Burst Initiation and Polymerase Pause Release Are Key Control Points of Transcriptional Regulation

3D chromatin architecture, BRD4, and Mediator have distinct roles in regulating genome-wide transcriptional bursting and gene network

Discontinuous transcription is evolutionarily conserved and a fundamental feature of gene regulation; yet, the exact mechanisms underlying transcriptional bursting are unresolved. Analyses of bursting transcriptome-wide have focused on the role of cis-regulatory elements, but other factors that regulate this process remain elusive. We applied mathematical modeling to single-cell RNA sequencing data to infer bursting dynamics transcriptome-wide under multiple conditions to identify possible molecular mechanisms. We found that Mediator complex subunit 26 (MED26) primarily regulates frequency, MYC regulates burst size, while cohesin and Bromodomain-containing protein 4 (BRD4) can modulate both. Despite comparable effects on RNA levels among these perturbations, acute depletion of MED26 had the most profound impact on the entire gene regulatory network, acting downstream of chromatin spatial architecture and without affecting TATA box-binding protein (TBP) recruitment. These results indicate that later steps in the initiation of transcriptional bursts are primary nodes for integrating gene networks in single cells.

Polyploidisation pleiotropically buffers ageing in hepatocytes

BACKGROUND & AIMS

Polyploidy in hepatocytes has been proposed as a genetic mechanism to buffer against transcriptional dysregulation. Here, we aim to demonstrate the role of polyploidy in modulating gene regulatory networks in hepatocytes during ageing.

METHODS

We performed single-nucleus RNA sequencing in hepatocyte nuclei of different ploidy levels isolated from young and old wild-type mice. Changes in the gene expression and regulatory network were compared to three independent strains that were haploinsufficient for HNF4A, CEBPA or CTCF, representing non-deleterious perturbations. Phenotypic characteristics of the liver section were additionally evaluated histologically, whereas the genomic allele composition of hepatocytes was analysed by BaseScope.

RESULTS

We observed that ageing in wild-type mice results in nuclei polyploidy and a marked increase in steatosis. Haploinsufficiency of liver-specific master regulators (HFN4A or CEBPA) results in the enrichment of hepatocytes with tetraploid nuclei at a young age, affecting the genomic regulatory network, and dramatically suppressing ageing-related steatosis tissue wide. Notably, these phenotypes are not the result of subtle disruption to liver-specific transcriptional networks, since haploinsufficiency in the CTCF insulator protein resulted in the same phenotype. Further quantification of genotypes of tetraploid hepatocytes in young and old HFN4A-haploinsufficient mice revealed that during ageing, tetraploid hepatocytes lead to the selection of wild-type alleles, restoring non-deleterious genetic perturbations.

CONCLUSIONS

Our results suggest a model whereby polyploidisation leads to fundamentally different cell states. Polyploid conversion enables pleiotropic buffering against age-related decline via non-random allelic segregation to restore a wild-type genome.

IMPACT AND IMPLICATIONS

The functional role of hepatocyte polyploidisation during ageing is poorly understood. Using single-nucleus RNA sequencing and BaseScope approaches, we have studied ploidy dynamics during ageing in murine livers with non-deleterious genetic perturbations. We have identified that hepatocytes present different cellular states and the ability to buffer ageing-associated dysfunctions. Tetraploid nuclei exhibit robust transcriptional networks and are better adapted to genomically overcome perturbations. Novel therapeutic interventions aimed at attenuating age-related changes in tissue function could be exploited by manipulation of ploidy dynamics during chronic liver conditions.

Stochastic Modeling of Biophysical Responses to Perturbation

Recent advances in high-throughput, multi-condition experiments allow for genome-wide investigation of how perturbations affect transcription and translation in the cell across multiple biological entities or modalities, from chromatin and mRNA information to protein production and spatial morphology. This presents an unprecedented opportunity to unravel how the processes of DNA and RNA regulation direct cell fate determination and disease response. Most methods designed for analyzing large-scale perturbation data focus on the observational outcomes, e.g., expression; however, many potential transcriptional mechanisms, such as transcriptional bursting or splicing dynamics, can underlie these complex and noisy observations. In this analysis, we demonstrate how a stochastic biophysical modeling approach to interpreting high-throughout perturbation data enables deeper investigation of the 'how' behind such molecular measurements. Our approach takes advantage of modalities already present in data produced with current technologies, such as nascent and mature mRNA measurements, to illuminate transcriptional dynamics induced by perturbation, predict kinetic behaviors in new perturbation settings, and uncover novel populations of cells with distinct kinetic responses to perturbation.

Analysis of a detailed multi-stage model of stochastic gene expression using queueing theory and model reduction

We introduce a biologically detailed, stochastic model of gene expression describing the multiple rate-limiting steps of transcription, nuclear pre-mRNA processing, nuclear mRNA export, cytoplasmic mRNA degradation and translation of mRNA into protein. The processes in sub-cellular compartments are described by an arbitrary number of processing stages, thus accounting for a significantly finer molecular description of gene expression than conventional models such as the telegraph, two-stage and three-stage models of gene expression. We use two distinct tools, queueing theory and model reduction using the slow-scale linear-noise approximation, to derive exact or approximate analytic expressions for the moments or distributions of nuclear mRNA, cytoplasmic mRNA and protein fluctuations, as well as lower bounds for their Fano factors in steady-state conditions. We use these to study the phase diagram of the stochastic model; in particular we derive parametric conditions determining three types of transitions in the properties of mRNA fluctuations: from sub-Poissonian to super-Poissonian noise, from high noise in the nucleus to high noise in the cytoplasm, and from a monotonic increase to a monotonic decrease of the Fano factor with the number of processing stages. In contrast, protein fluctuations are always super-Poissonian and show weak dependence on the number of mRNA processing stages. Our results delineate the region of parameter space where conventional models give qualitatively incorrect results and provide insight into how the number of processing stages, e.g. the number of rate-limiting steps in initiation, splicing and mRNA degradation, shape stochastic gene expression by modulation of molecular memory.

Identification of molecular determinants of gene-specific bursting patterns by high-throughput imaging screens

Stochastic transcriptional bursting is a universal property of active genes. While different genes exhibit distinct bursting patterns, the molecular mechanisms for gene-specific stochastic bursting are largely unknown. We have developed and applied a high-throughput-imaging based screening strategy to identify cellular factors and molecular mechanisms that determine the bursting behavior of human genes. Focusing on epigenetic regulators, we find that protein acetylation is a strong acute modulator of burst frequency, burst size and heterogeneity of bursting. Acetylation globally affects the Off-time of genes but has gene-specific effects on the On-time. Yet, these effects are not strongly linked to promoter acetylation, which do not correlate with bursting properties, and forced promoter acetylation has variable effects on bursting. Instead, we demonstrate acetylation of the Integrator complex as a key determinant of gene bursting. Specifically, we find that elevated Integrator acetylation decreases bursting frequency. Taken together our results suggest a prominent role of non-histone proteins in determining gene bursting properties, and they identify histone-independent acetylation of a transcription cofactor as an allosteric modulator of bursting via a far-downstream bursting checkpoint.

Nuclear patterns of phosphatidylinositol 4,5- and 3,4-bisphosphate revealed by super-resolution microscopy differ between the consecutive stages of RNA polymerase II transcription

Phosphatidylinositol phosphates are powerful signaling molecules that orchestrate signaling and direct membrane trafficking in the cytosol. Interestingly, phosphatidylinositol phosphates also localize within the membrane-less compartments of the cell nucleus, where they participate in the regulation of gene expression. Nevertheless, current models of gene expression, which include condensates of proteins and nucleic acids, do not include nuclear phosphatidylinositol phosphates. This gap is partly a result of the missing detailed analysis of the subnuclear distribution of phosphatidylinositol phosphates and their relationships with gene expression. Here, we used quantitative dual-color direct stochastic optical reconstruction microscopy to analyze the nanoscale co-patterning between RNA polymerase II transcription initiation and elongation markers with respect to phosphatidylinositol 4,5- or 3,4-bisphosphate in the nucleoplasm and nuclear speckles and compared it with randomized data and cells with inhibited transcription. We found specific co-patterning of the transcription initiation marker P-S5 with phosphatidylinositol 4,5-bisphosphate in the nucleoplasm and with phosphatidylinositol 3,4-bisphosphate at the periphery of nuclear speckles. We showed the specific accumulation of the transcription elongation marker PS-2 and of nascent RNA in the proximity of phosphatidylinositol 3,4-bisphosphate associated with nuclear speckles. Taken together, this shows that the distinct spatial associations between the consecutive stages of RNA polymerase II transcription and nuclear phosphatidylinositol phosphates exhibit specificity within the gene expression compartments. Thus, in analogy to the cellular membranes, where phospholipid composition orchestrates signaling pathways and directs membrane trafficking, we propose a model in which the phospholipid identity of gene expression compartments orchestrates RNA polymerase II transcription.

Solving stochastic gene-expression models using queueing theory: A tutorial review

Stochastic models of gene expression are typically formulated using the chemical master equation, which can be solved exactly or approximately using a repertoire of analytical methods. Here, we provide a tutorial review of an alternative approach based on queueing theory that has rarely been used in the literature of gene expression. We discuss the interpretation of six types of infinite-server queues from the angle of stochastic single-cell biology and provide analytical expressions for the stationary and nonstationary distributions and/or moments of mRNA/protein numbers and bounds on the Fano factor. This approach may enable the solution of complex models that have hitherto evaded analytical solution.

Mitigating transcription noise via protein sharing in syncytial cells

Bursty transcription allows nuclei to concentrate the work of transcribing mRNA into short, intermittent intervals, potentially reducing transcriptional interference. However, bursts of mRNA production can increase noise in protein abundances. Here, we formulate models for gene expression in syncytia, or multinucleate cells, showing that protein abundance noise may be mitigated locally via spatial averaging of diffuse proteins. Our modeling shows a universal reduction in protein noise, which increases with the average number of nuclei per cell and persists even when the number of nuclei is itself a random variable. Experimental data comparing distributions of a cyclin mRNA that is conserved between brewer's yeast and a closely related filamentous fungus Ashbya gossypii confirm that syncytism is permissive of greater levels of transcriptional noise. Our findings suggest that division of transcriptional labor between nuclei allows syncytia to sidestep tradeoffs between efficiency and precision of gene expression.

Enhancer-promoter specificity in gene transcription: molecular mechanisms and disease associations

Although often located at a distance from their target gene promoters, enhancers are the primary genomic determinants of temporal and spatial transcriptional specificity in metazoans. Since the discovery of the first enhancer element in simian virus 40, there has been substantial interest in unraveling the mechanism(s) by which enhancers communicate with their partner promoters to ensure proper gene expression. These research efforts have benefited considerably from the application of increasingly sophisticated sequencing- and imaging-based approaches in conjunction with innovative (epi)genome-editing technologies; however, despite various proposed models, the principles of enhancer-promoter interaction have still not been fully elucidated. In this review, we provide an overview of recent progress in the eukaryotic gene transcription field pertaining to enhancer-promoter specificity. A better understanding of the mechanistic basis of lineage- and context-dependent enhancer-promoter engagement, along with the continued identification of functional enhancers, will provide key insights into the spatiotemporal control of gene expression that can reveal therapeutic opportunities for a range of enhancer-related diseases.

Power-law behavior of transcriptional bursting regulated by enhancer-promoter communication

Revealing how transcriptional bursting kinetics are genomically encoded is challenging because genome structures are stochastic at the organization level and are suggestively linked to gene transcription. To address this challenge, we develop a generic theoretical framework that integrates chromatin dynamics, enhancer-promoter (E-P) communication, and gene-state switching to study transcriptional bursting. The theory predicts that power law can be a general rule to quantitatively describe bursting modulations by E-P spatial communication. Specifically, burst frequency and burst size are up-regulated by E-P communication strength, following power laws with positive exponents. Analysis of the scaling exponents further reveals that burst frequency is preferentially regulated. Bursting kinetics are down-regulated by E-P genomic distance with negative power-law exponents, and this negative modulation desensitizes at large distances. The mutual information between burst frequency (or burst size) and E-P spatial distance further reveals essential characteristics of the information transfer from E-P communication to transcriptional bursting kinetics. These findings, which are in agreement with experimental observations, not only reveal fundamental principles of E-P communication in transcriptional bursting but also are essential for understanding cellular decision-making.

Time will tell: comparing timescales to gain insight into transcriptional bursting

Recent imaging studies have captured the dynamics of regulatory events of transcription inside living cells. These events include transcription factor (TF) DNA binding, chromatin remodeling and modification, enhancer-promoter (E-P) proximity, cluster formation, and preinitiation complex (PIC) assembly. Together, these molecular events culminate in stochastic bursts of RNA synthesis, but their kinetic relationship remains largely unclear. In this review, we compare the timescales of upstream regulatory steps (input) with the kinetics of transcriptional bursting (output) to generate mechanistic models of transcription dynamics in single cells. We highlight open questions and potential technical advances to guide future endeavors toward a quantitative and kinetic understanding of transcription regulation.

ChIP-DIP: A multiplexed method for mapping hundreds of proteins to DNA uncovers diverse regulatory elements controlling gene expression

Gene expression is controlled by the dynamic localization of thousands of distinct regulatory proteins to precise regions of DNA. Understanding this cell-type specific process has been a goal of molecular biology for decades yet remains challenging because most current DNA-protein mapping methods study one protein at a time. To overcome this, we developed ChIP-DIP (ChIP Done In Parallel), a split-pool based method that enables simultaneous, genome-wide mapping of hundreds of diverse regulatory proteins in a single experiment. We demonstrate that ChIP-DIP generates highly accurate maps for all classes of DNA-associated proteins, including histone modifications, chromatin regulators, transcription factors, and RNA Polymerases. Using these data, we explore quantitative combinations of protein localization on genomic DNA to define distinct classes of regulatory elements and their functional activity. Our data demonstrate that ChIP-DIP enables the generation of 'consortium level', context-specific protein localization maps within any molecular biology lab.

4D nucleome equation predicts gene expression controlled by long-range enhancer-promoter interaction

Recent experimental evidence strongly supports that three-dimensional (3D) long-range enhancer-promoter (E-P) interactions have important influences on gene-expression dynamics, but it is unclear how the interaction information is translated into gene expression over time (4D). To address this question, we developed a general theoretical framework (named as a 4D nucleome equation), which integrates E-P interactions on chromatin and biochemical reactions of gene transcription. With this equation, we first present the distribution of mRNA counts as a function of the E-P genomic distance and then reveal a power-law scaling of the expression level in this distance. Interestingly, we find that long-range E-P interactions can induce bimodal and trimodal mRNA distributions. The 4D nucleome equation also allows for model selection and parameter inference. When this equation is applied to the mouse embryonic stem cell smRNA-FISH data and the E-P genomic-distance data, the predicted E-P contact probability and mRNA distribution are in good agreement with experimental results. Further statistical inference indicates that the E-P interactions prefer to modulate the mRNA level by controlling promoter activation and transcription initiation rates. Our model and results provide quantitative insights into both spatiotemporal gene-expression determinants (i.e., long-range E-P interactions) and cellular fates during development.

Model-based characterization of the equilibrium dynamics of transcription initiation and promoter-proximal pausing in human cells

In metazoans, both transcription initiation and the escape of RNA polymerase (RNAP) from promoter-proximal pausing are key rate-limiting steps in gene expression. These processes play out at physically proximal sites on the DNA template and appear to influence one another through steric interactions. Here, we examine the dynamics of these processes using a combination of statistical modeling, simulation, and analysis of real nascent RNA sequencing data. We develop a simple probabilistic model that jointly describes the kinetics of transcription initiation, pause-escape, and elongation, and the generation of nascent RNA sequencing read counts under steady-state conditions. We then extend this initial model to allow for variability across cells in promoter-proximal pause site locations and steric hindrance of transcription initiation from paused RNAPs. In an extensive series of simulations, we show that this model enables accurate estimation of initiation and pause-escape rates. Furthermore, we show by simulation and analysis of real data that pause-escape is often strongly rate-limiting and that steric hindrance can dramatically reduce initiation rates. Our modeling framework is applicable to a variety of inference problems, and our software for estimation and simulation is freely available.

Poisson representation: a bridge between discrete and continuous models of stochastic gene regulatory networks

Stochastic gene expression dynamics can be modelled either discretely or continuously. Previous studies have shown that the mRNA or protein number distributions of some simple discrete and continuous gene expression models are related by Gardiner's Poisson representation. Here, we systematically investigate the Poisson representation in complex stochastic gene regulatory networks. We show that when the gene of interest is unregulated, the discrete and continuous descriptions of stochastic gene expression are always related by the Poisson representation, no matter how complex the model is. This generalizes the results obtained in Dattani & Barahona (Dattani & Barahona 2017 J. R. Soc. Interface 14, 20160833 (doi:10.1098/rsif.2016.0833)). In addition, using a simple counter-example, we find that the Poisson representation in general fails to link the two descriptions when the gene is regulated. However, for a general stochastic gene regulatory network, we demonstrate that the discrete and continuous models are approximately related by the Poisson representation in the limit of large protein numbers. These theoretical results are further applied to analytically solve many complex gene expression models whose exact distributions are previously unknown.

Mathematical Models of HIV-1 Dynamics, Transcription, and Latency

HIV-1 latency is a major barrier to curing infections with antiretroviral therapy and, consequently, to eliminating the disease globally. The establishment, maintenance, and potential clearance of latent infection are complex dynamic processes and can be best described with the help of mathematical models followed by experimental validation. Here, we review the use of viral dynamics models for HIV-1, with a focus on applications to the latent reservoir. Such models have been used to explain the multi-phasic decay of viral load during antiretroviral therapy, the early seeding of the latent reservoir during acute infection and the limited inflow during treatment, the dynamics of viral blips, and the phenomenon of post-treatment control. Finally, we discuss that mathematical models have been used to predict the efficacy of potential HIV-1 cure strategies, such as latency-reversing agents, early treatment initiation, or gene therapies, and to provide guidance for designing trials of these novel interventions.

Lola-I is a promoter pioneer factor that establishes de novo Pol II pausing during development

While the accessibility of enhancers is dynamically regulated during development, promoters tend to be constitutively accessible and poised for activation by paused Pol II. By studying Lola-I, a Drosophila zinc finger transcription factor, we show here that the promoter state can also be subject to developmental regulation independently of gene activation. Lola-I is ubiquitously expressed at the end of embryogenesis and causes its target promoters to become accessible and acquire paused Pol II throughout the embryo. This promoter transition is required but not sufficient for tissue-specific target gene activation. Lola-I mediates this function by depleting promoter nucleosomes, similar to the action of pioneer factors at enhancers. These results uncover a level of regulation for promoters that is normally found at enhancers and reveal a mechanism for the de novo establishment of paused Pol II at promoters.

Regulation of Pol II Pausing during Daily Gene Transcription in Mouse Liver

Cell autonomous circadian oscillation is present in central and various peripheral tissues. The intrinsic tissue clock and various extrinsic cues drive gene expression rhythms. Transcription regulation is thought to be the main driving force for gene rhythms. However, how transcription rhythms arise remains to be fully characterized due to the fact that transcription is regulated at multiple steps. In particular, Pol II recruitment, pause release, and premature transcription termination are critical regulatory steps that determine the status of Pol II pausing and transcription output near the transcription start site (TSS) of the promoter. Recently, we showed that Pol II pausing exhibits genome-wide changes during daily transcription in mouse liver. In this article, we review historical as well as recent findings on the regulation of transcription rhythms by the circadian clock and other transcription factors, and the potential limitations of those results in explaining rhythmic transcription at the TSS. We then discuss our results on the genome-wide characteristics of daily changes in Pol II pausing, the possible regulatory mechanisms involved, and their relevance to future research on circadian transcription regulation.

Single-cell transcriptional uncertainty landscape of cell differentiation

Background: Single-cell studies have demonstrated the presence of significant cell-to-cell heterogeneity in gene expression. Whether such heterogeneity is only a bystander or has a functional role in the cell differentiation process is still hotly debated. Methods: In this study, we quantified and followed single-cell transcriptional uncertainty - a measure of gene transcriptional stochasticity in single cells - in 10 cell differentiation systems of varying cell lineage progressions, from single to multi-branching trajectories, using the stochastic two-state gene transcription model. Results: By visualizing the transcriptional uncertainty as a landscape over a two-dimensional representation of the single-cell gene expression data, we observed universal features in the cell differentiation trajectories that include: (i) a peak in single-cell uncertainty during transition states, and in systems with bifurcating differentiation trajectories, each branching point represents a state of high transcriptional uncertainty; (ii) a positive correlation of transcriptional uncertainty with transcriptional burst size and frequency; (iii) an increase in RNA velocity preceding the increase in the cell transcriptional uncertainty. Conclusions: Our findings suggest a possible universal mechanism during the cell differentiation process, in which stem cells engage stochastic exploratory dynamics of gene expression at the start of the cell differentiation by increasing gene transcriptional bursts, and disengage such dynamics once cells have decided on a particular terminal cell identity. Notably, the peak of single-cell transcriptional uncertainty signifies the decision-making point in the cell differentiation process.

Predictive model of transcriptional elongation control identifies trans regulatory factors from chromatin signatures

Promoter-proximal Polymerase II (Pol II) pausing is a key rate-limiting step for gene expression. DNA and RNA-binding trans-acting factors regulating the extent of pausing have been identified. However, we lack a quantitative model of how interactions of these factors determine pausing, therefore the relative importance of implicated factors is unknown. Moreover, previously unknown regulators might exist. Here we address this gap with a machine learning model that accurately predicts the extent of promoter-proximal Pol II pausing from large-scale genome and transcriptome binding maps and gene annotation and sequence composition features. We demonstrate high accuracy and generalizability of the model by validation on an independent cell line which reveals the model's cell line agnostic character. Model interpretation in light of prior knowledge about molecular functions of regulatory factors confirms the interconnection of pausing with other RNA processing steps. Harnessing underlying feature contributions, we assess the relative importance of each factor, quantify their predictive effects and systematically identify previously unknown regulators of pausing. We additionally identify 16 previously unknown 7SK ncRNA interacting RNA-binding proteins predictive of pausing. Our work provides a framework to further our understanding of the regulation of the critical early steps in transcriptional elongation.

PIP2-Effector Protein MPRIP Regulates RNA Polymerase II Condensation and Transcription

The specific post-translational modifications of the C-terminal domain (CTD) of the Rpb1 subunit of RNA polymerase II (RNAPII) correlate with different stages of transcription. The phosphorylation of the Ser5 residues of this domain associates with the initiation condensates, which are formed through liquid-liquid phase separation (LLPS). The subsequent Tyr1 phosphorylation of the CTD peaks at the promoter-proximal region and is involved in the pause-release of RNAPII. By implementing super-resolution microscopy techniques, we previously reported that the nuclear Phosphatidylinositol 4,5-bisphosphate (PIP2) associates with the Ser5-phosphorylated-RNAPII complex and facilitates the RNAPII transcription. In this study, we identified Myosin Phosphatase Rho-Interacting Protein (MPRIP) as a novel regulator of the RNAPII transcription that recruits Tyr1-phosphorylated CTD (Tyr1P-CTD) to nuclear PIP2-containing structures. The depletion of MPRIP increases the number of the initiation condensates, indicating a defect in the transcription. We hypothesize that MPRIP regulates the condensation and transcription through affecting the association of the RNAPII complex with nuclear PIP2-rich structures. The identification of Tyr1P-CTD as an interactor of PIP2 and MPRIP further points to a regulatory role in RNAPII pause-release, where the susceptibility of the transcriptional complex to leave the initiation condensate depends on its association with nuclear PIP2-rich structures. Moreover, the N-terminal domain of MPRIP, which is responsible for the interaction with the Tyr1P-CTD, contains an F-actin binding region that offers an explanation of how nuclear F-actin formations can affect the RNAPII transcription and condensation. Overall, our findings shed light on the role of PIP2 in RNAPII transcription through identifying the F-actin binding protein MPRIP as a transcription regulator and a determinant of the condensation of RNAPII.

From structure to molecular condensates: emerging mechanisms for Mediator function

Mediator is a large modular protein assembly whose function as a coactivator of transcription is conserved in all eukaryotes. The Mediator complex can integrate and relay signals from gene-specific activators bound at enhancers to activate the general transcription machinery located at promoters. It has thus been described as a bridge between these elements during initiation of transcription. Here, we review recent studies on Mediator relating to its structure, gene specificity and general requirement, roles in chromatin architecture as well as novel concepts involving phase separation and transcriptional bursting. We revisit the mechanism of action of Mediator and ultimately put forward models for its mode of action in gene activation.

STREAMING-Tag System: Technology to Enable Visualization of Transcriptional Activity and Subnuclear Localization of Specific Endogenous Genes

The Spliced TetO REpeAt, MS2 repeat, and INtein sandwiched reporter Gene tag (STREAMING-tag) system enables imaging of nuclear localization as well as the transcription activity of a specific endogenous gene at sub-100-nm resolution in living cells. The use of this system combined with imaging of epigenome states enables a detailed analysis of the impact of epigenome status on transcriptional dynamics. In this chapter, we describe a method for quantifying distances between Nanog gene and clusters of cofactor BRD4 using the STREAMING-tag system in mouse embryonic stem cells.

Emerging roles of BET proteins in transcription and co-transcriptional RNA processing

Transcription by RNA polymerase II (Pol II) gives rise to all nuclear protein-coding and a large set of non-coding RNAs, and is strictly regulated and coordinated with RNA processing. Bromodomain and extraterminal (BET) family proteins including BRD2, BRD3, and BRD4 have been implicated in the regulation of Pol II transcription in mammalian cells. However, only recent technological advances have allowed the analysis of direct functions of individual BET proteins with high precision in cells. These studies shed new light on the molecular mechanisms of transcription control by BET proteins challenging previous longstanding views. The most studied BET protein, BRD4, emerges as a master regulator of transcription elongation with roles also in coupling nascent transcription with RNA processing. In contrast, BRD2 is globally required for the formation of transcriptional boundaries to restrict enhancer activity to nearby genes. Although these recent findings suggest non-redundant functions of BRD4 and BRD2 in Pol II transcription, more research is needed for further clarification. Little is known about the roles of BRD3. Here, we illuminate experimental work that has initially linked BET proteins to Pol II transcription in mammalian cells, outline main methodological breakthroughs that have strongly advanced the understanding of BET protein functions, and discuss emerging roles of individual BET proteins in transcription and transcription-coupled RNA processing. Finally, we propose an updated model for the function of BRD4 in transcription and co-transcriptional RNA maturation. This article is categorized under: RNA Processing > 3' End Processing RNA Processing > Splicing Regulation/Alternative Splicing.

Genome-wide inference reveals that feedback regulations constrain promoter-dependent transcriptional burst kinetics

Gene expression in mammalian cells is highly variable and episodic, resulting in a series of discontinuous bursts of mRNAs. A challenge is to understand how static promoter architecture and dynamic feedback regulations dictate bursting on a genome-wide scale. Although single-cell RNA sequencing (scRNA-seq) provides an opportunity to address this challenge, effective analytical methods are scarce. We developed an interpretable and scalable inference framework, which combined experimental data with a mechanistic model to infer transcriptional burst kinetics (sizes and frequencies) and feedback regulations. Applying this framework to scRNA-seq data generated from embryonic mouse fibroblast cells, we found Simpson's paradoxes, i.e. genome-wide burst kinetics exhibit different characteristics in two cases without and with distinguishing feedback regulations. We also showed that feedbacks differently modulate burst frequencies and sizes and conceal the effects of transcription start site distributions on burst kinetics. Notably, only in the presence of positive feedback, TATA genes are expressed with high burst frequencies and enhancer-promoter interactions mainly modulate burst frequencies. The developed inference method provided a flexible and efficient way to investigate transcriptional burst kinetics and the obtained results would be helpful for understanding cell development and fate decision.

A structural mechanism of nuclear receptor biased agonism

Efforts to decrease the adverse effects of nuclear receptor (NR) drugs have yielded experimental agonists that produce better outcomes in mice. Some of these agonists have been shown to cause different, not just less intense, on-target transcriptomic effects; however, a structural explanation for such agonist-specific effects remains unknown. Here, we show that partial agonists of the NR peroxisome proliferator-associated receptor γ (PPARγ), which induce better outcomes in mice compared to clinically utilized type II diabetes PPARγ-binding drugs thiazolidinediones (TZDs), also favor a different group of coactivator peptides than the TZDs. We find that PPARγ full agonists can also be biased relative to each other in terms of coactivator peptide binding. We find differences in coactivator-PPARγ bonding between the coactivator subgroups which allow agonists to favor one group of coactivator peptides over another, including differential bonding to a C-terminal residue of helix 4. Analysis of all available NR-coactivator structures indicates that such differential helix 4 bonding persists across other NR-coactivator complexes, providing a general structural mechanism of biased agonism for many NRs. Further work will be necessary to determine if such bias translates into altered coactivator occupancy and physiology in cells.

The Mediator complex as a master regulator of transcription by RNA polymerase II

The Mediator complex, which in humans is 1.4 MDa in size and includes 26 subunits, controls many aspects of RNA polymerase II (Pol II) function. Apart from its size, a defining feature of Mediator is its intrinsic disorder and conformational flexibility, which contributes to its ability to undergo phase separation and to interact with a myriad of regulatory factors. In this Review, we discuss Mediator structure and function, with emphasis on recent cryogenic electron microscopy data of the 4.0-MDa transcription preinitiation complex. We further discuss how Mediator and sequence-specific DNA-binding transcription factors enable enhancer-dependent regulation of Pol II function at distal gene promoters, through the formation of molecular condensates (or transcription hubs) and chromatin loops. Mediator regulation of Pol II reinitiation is also discussed, in the context of transcription bursting. We propose a working model for Mediator function that combines experimental results and theoretical considerations related to enhancer-promoter interactions, which reconciles contradictory data regarding whether enhancer-promoter communication is direct or indirect. We conclude with a discussion of Mediator's potential as a therapeutic target and of future research directions.

A transcriptional cycling model recapitulates chromatin-dependent features of noisy inducible transcription

Activation of gene expression in response to environmental cues results in substantial phenotypic heterogeneity between cells that can impact a wide range of outcomes including differentiation, viral activation, and drug resistance. An important source of gene expression noise is transcriptional bursting, or the process by which transcripts are produced during infrequent bursts of promoter activity. Chromatin accessibility impacts transcriptional bursting by regulating the assembly of transcription factor and polymerase complexes on promoters, suggesting that the effect of an activating signal on transcriptional noise will depend on the initial chromatin state at the promoter. To explore this possibility, we simulated transcriptional activation using a transcriptional cycling model with three promoter states that represent chromatin remodeling, polymerase binding and pause release. We initiated this model over a large parameter range representing target genes with different chromatin environments, and found that, upon increasing the polymerase pause release rate to activate transcription, changes in gene expression noise varied significantly across initial promoter states. This model captured phenotypic differences in activation of latent HIV viruses integrated at different chromatin locations and mediated by the transcription factor NF-κB. Activating transcription in the model via increasing one or more of the transcript production rates, as occurs following NF-κB activation, reproduced experimentally measured transcript distributions for four different latent HIV viruses, as well as the bimodal pattern of HIV protein expression that leads to a subset of reactivated virus. Importantly, the parameter ‘activation path’ differentially affected gene expression noise, and ultimately viral activation, in line with experimental observations. This work demonstrates how upstream signaling pathways can be connected to biological processes that underlie transcriptional bursting, resulting in target gene-specific noise profiles following stimulation of a single upstream pathway.

Many genes are transcribed in infrequent bursts of mRNA production through a process called transcriptional bursting, which contributes to variability in responses between cells. Heterogeneity in cell responses can have important biological impacts, such as whether a cell supports viral replication or responds to a drug, and thus there is an effort to describe this process with mathematical models to predict biological outcomes. Previous models described bursting as a transition between an “OFF” state or an “ON” state, an elegant and simple mathematical representation of complex molecular mechanisms, but one which failed to capture how upstream activation signals affected bursting. To address this, we added an additional promoter state to better reflect biological mechanisms underlying bursting. By fitting this model to variable activation of quiescent HIV infections in T cells, we showed that our model more accurately described viral expression variability across cells in response to an upstream stimulus. Our work highlights how mathematical models can be further developed to understand complex biological mechanisms and suggests ways to connect transcriptional bursting to upstream activation pathways.

BRD4: a general regulator of transcription elongation

Transcription elongation by RNA polymerase II (Pol II) has emerged as a regulatory hub in gene expression. A key control point occurs during early transcription elongation when Pol II pauses in the promoter-proximal region at the majority of genes in mammalian cells and at a large set of genes in Drosophila. An increasing number of trans-acting factors have been linked to promoter-proximal pausing. Some factors help to establish the pause, whereas others are required for the release of Pol II into productive elongation. A dysfunction of this elongation control point leads to aberrant gene expression and can contribute to disease development. The BET bromodomain protein BRD4 has been implicated in elongation control. However, only recently direct BRD4-specific functions in Pol II transcription elongation have been uncovered. This mainly became possible with technological advances that allow selective and rapid ablation of BRD4 in cells along with the availability of approaches that capture the immediate consequences on nascent transcription. This review sheds light on the experimental breakthroughs that led to the emerging view of BRD4 as a general regulator of transcription elongation.

Inferring gene regulation from stochastic transcriptional variation across single cells at steady state

Regulatory relationships between transcription factors (TFs) and their target genes lie at the heart of cellular identity and function; however, uncovering these relationships is often labor-intensive and requires perturbations. Here, we propose a principled framework to systematically infer gene regulation for all TFs simultaneously in cells at steady state by leveraging the intrinsic variation in the transcriptional abundance across single cells. Through modeling and simulations, we characterize how transcriptional bursts of a TF gene are propagated to its target genes, including the expected ranges of time delay and magnitude of maximum covariation. We distinguish these temporal trends from the time-invariant covariation arising from cell states, and we delineate the experimental and technical requirements for leveraging these small but meaningful cofluctuations in the presence of measurement noise. While current technology does not yet allow adequate power for definitively detecting regulatory relationships for all TFs simultaneously in cells at steady state, we investigate a small-scale dataset to inform future experimental design. This study supports the potential value of mapping regulatory connections through stochastic variation, and it motivates further technological development to achieve its full potential.

Stochastic gene transcription with non-competitive transcription regulatory architecture

The transcription factors, such as activators and repressors, can interact with the promoter of gene either in a competitive or non-competitive way. In this paper, we construct a stochastic model with non-competitive transcriptional regulatory architecture and develop an analytical theory that re-establishes the experimental results with an improved data fitting. The analytical expressions in the theory allow us to study the nature of the system corresponding to any of its parameters and hence, enable us to find out the factors that govern the regulation of gene expression for that architecture. We notice that, along with transcriptional reinitiation and repressors, there are other parameters that can control the noisiness of this network. We also observe that, the Fano factor (at mRNA level) varies from sub-Poissonian regime to super-Poissonian regime. In addition to the aforementioned properties, we observe some anomalous characteristics of the Fano factor (at mRNA level) and that of the variance of protein at lower activator concentrations in the presence of repressor molecules. This model is useful to understand the architecture of interactions which may buffer the stochasticity inherent to gene transcription.

Stochastic Transcription with Alterable Synthesis Rates

Background: Gene transcription is a random bursting process that leads to large variability in mRNA numbers in single cells. The main cause is largely attributed to random switching between periods of active and inactive gene transcription. In some experiments, it has been observed that variation in the number of active transcription sites causes the initiation rate to vary during elongation. Results: We established a mathematical model based on the molecular reaction mechanism in single cells and studied a stochastic transcription system consisting of two active states and one inactive state, in which mRNA molecules are produced with two different synthesis rates. Conclusions: By calculation, we obtained the average mRNA expression level, the noise strength, and the skewness of transcripts. We gave a necessary and sufficient condition that causes the average mRNA level to peak at a limited time. The model could help us to distinguish an appropriate mechanism that may be employed by cells to transcribe mRNA molecules. Our simulations were in agreement with some experimental data and showed that the skewness can measure the deviation of the distribution of transcripts from the mean value. Especially for mature mRNAs, their distributions were almost able to be determined by the mean, the noise (or the noise strength), and the skewness.

Transcription Pause and Escape in Neurodevelopmental Disorders

Transcription pause-release is an important, highly regulated step in the control of gene expression. Modulated by various factors, it enables signal integration and fine-tuning of transcriptional responses. Mutations in regulators of pause-release have been identified in a range of neurodevelopmental disorders that have several common features affecting multiple organ systems. This review summarizes current knowledge on this novel subclass of disorders, including an overview of clinical features, mechanistic details, and insight into the relevant neurodevelopmental processes.

Systematic inference identifies a major source of heterogeneity in cell signaling dynamics: The rate-limiting step number

Identifying the sources of cell-to-cell variability in signaling dynamics is essential to understand drug response variability and develop effective therapeutics. However, it is challenging because not all signaling intermediate reactions can be experimentally measured simultaneously. This can be overcome by replacing them with a single random time delay, but the resulting process is non-Markovian, making it difficult to infer cell-to-cell heterogeneity in reaction rates and time delays. To address this, we developed an efficient and scalable moment-based Bayesian inference method (MBI) with a user-friendly computational package that infers cell-to-cell heterogeneity in the non-Markovian signaling process. We applied MBI to single-cell expression profiles from promoters responding to antibiotics and discovered a major source of cell-to-cell variability in antibiotic stress response: the number of rate-limiting steps in signaling cascades. This knowledge can help identify effective therapies that destroy all pathogenic or cancer cells, and the approach can be applied to precision medicine.

A fast Myosin super enhancer dictates muscle fiber phenotype through competitive interactions with Myosin genes

The contractile properties of adult myofibers are shaped by their Myosin heavy chain isoform content. Here, we identify by snATAC-seq a 42 kb super-enhancer at the locus regrouping the fast Myosin genes. By 4C-seq we show that active fast Myosin promoters interact with this super-enhancer by DNA looping, leading to the activation of a single promoter per nucleus. A rainbow mouse transgenic model of the locus including the super-enhancer recapitulates the endogenous spatio-temporal expression of adult fast Myosin genes. In situ deletion of the super-enhancer by CRISPR/Cas9 editing demonstrates its major role in the control of associated fast Myosin genes, and deletion of two fast Myosin genes at the locus reveals an active competition of the promoters for the shared super-enhancer. Last, by disrupting the organization of fast Myosin, we uncover positional heterogeneity within limb skeletal muscles that may underlie selective muscle susceptibility to damage in certain myopathies.

The contractile properties of adult myofibers are shaped by their Myosin heavy chain isoform content. Here the authors show that a super enhancer controls the spatiotemporal expression of the genes at the fast myosin heavy chain locus by DNA looping and that this expression profile is recapitulated in a rainbow transgenic mouse model of the locus.

Structural visualization of de novo transcription initiation by Saccharomyces cerevisiae RNA polymerase II

Previous structural studies of the initiation-elongation transition of RNA polymerase II (pol II) transcription have relied on the use of synthetic oligonucleotides, often artificially discontinuous to capture pol II in the initiating state. Here, we report multiple structures of initiation complexes converted de novo from a 33-subunit yeast pre-initiation complex (PIC) through catalytic activities and subsequently stalled at different template positions. We determine that PICs in the initially transcribing complex (ITC) can synthesize a transcript of ∼26 nucleotides before transitioning to an elongation complex (EC) as determined by the loss of general transcription factors (GTFs). Unexpectedly, transition to an EC was greatly accelerated when an ITC encountered a downstream EC stalled at promoter proximal regions and resulted in a collided head-to-end dimeric EC complex. Our structural analysis reveals a dynamic state of TFIIH, the largest of GTFs, in PIC/ITC with distinct functional consequences at multiple steps on the pathway to elongation.

Distinct transcription kinetics of pluripotent cell states

Mouse embryonic stem cells (mESCs) can adopt naïve, ground, and paused pluripotent states that give rise to unique transcriptomes. Here, we use transient transcriptome sequencing (TT-seq) to define both coding and non-coding transcription units (TUs) in these three pluripotent states and combine TT-seq with RNA polymerase II occupancy profiling to unravel the kinetics of RNA metabolism genome-wide. Compared to the naïve state (serum), RNA synthesis and turnover rates are globally reduced in the ground state (2i) and the paused state (mTORi). The global reduction in RNA synthesis goes along with a genome-wide decrease of polymerase elongation velocity, which is related to epigenomic features and alterations in the Pol II termination window. Our data suggest that transcription activity is the main determinant of steady state mRNA levels in the naïve state and that genome-wide changes in transcription kinetics invoke ground and paused pluripotent states.

RNA polymerase II pausing in development: orchestrating transcription

The coordinated regulation of transcriptional networks underpins cellular identity and developmental progression. RNA polymerase II promoter-proximal pausing (Pol II pausing) is a prevalent mechanism by which cells can control and synchronize transcription. Pol II pausing regulates the productive elongation step of transcription at key genes downstream of a variety of signalling pathways, such as FGF and Nodal. Recent advances in our understanding of the Pol II pausing machinery and its role in transcription call for an assessment of these findings within the context of development. In this review, we discuss our current understanding of the molecular basis of Pol II pausing and its function during organismal development. By critically assessing the tools used to study this process we conclude that combining recently developed genomics approaches with refined perturbation systems has the potential to expand our understanding of Pol II pausing mechanistically and functionally in the context of development and beyond.

Modeling population size independent tissue epigenomes by ChIL-seq with single thin sections

Recent advances in genome‐wide technologies have enabled analyses using small cell numbers of even single cells. However, obtaining tissue epigenomes with cell‐type resolution from large organs and tissues still remains challenging, especially when the available material is limited. Here, we present a ChIL‐based approach for analyzing the diverse cellular dynamics at the tissue level using high‐depth epigenomic data. “ChIL for tissues” allows the analysis of a single tissue section and can reproducibly generate epigenomic profiles from several tissue types, based on the distribution of target epigenomic states, tissue morphology, and number of cells. The proposed method enabled the independent evaluation of changes in cell populations and gene activation in cells from regenerating skeletal muscle tissues, using a statistical model of RNA polymerase II distribution on gene loci. Thus, the integrative analyses performed using ChIL can elucidate in vivo cell‐type dynamics of tissues.

STL-seq reveals pause-release and termination kinetics for promoter-proximal paused RNA polymerase II transcripts

Despite the critical regulatory function of promoter-proximal pausing, the influence of pausing kinetics on transcriptional control remains an active area of investigation. Here, we present Start-TimeLapse-seq (STL-seq), a method that captures the genome-wide kinetics of short, capped RNA turnover and reveals principles of regulation at the pause site. By measuring the rates of release into elongation and premature termination through the inhibition of pause release, we determine that pause-release rates are highly variable, and most promoter-proximal paused RNA polymerase II molecules prematurely terminate (∼80%). The preferred regulatory mechanism upon a hormonal stimulus (20-hydroxyecdysone) is to influence pause-release rather than termination rates. Transcriptional shutdown occurs concurrently with the induction of promoter-proximal termination under hyperosmotic stress, but paused transcripts from TATA box-containing promoters remain stable, demonstrating an important role for cis-acting DNA elements in pausing. STL-seq dissects the kinetics of pause release and termination, providing an opportunity to identify mechanisms of transcriptional regulation.

The 3D Genome: From Structure to Function

The genome is the most functional part of a cell, and genomic contents are organized in a compact three-dimensional (3D) structure. The genome contains millions of nucleotide bases organized in its proper frame. Rapid development in genome sequencing and advanced microscopy techniques have enabled us to understand the 3D spatial organization of the genome. Chromosome capture methods using a ligation approach and the visualization tool of a 3D genome browser have facilitated detailed exploration of the genome. Topologically associated domains (TADs), lamin-associated domains, CCCTC-binding factor domains, cohesin, and chromatin structures are the prominent identified components that encode the 3D structure of the genome. Although TADs are the major contributors to 3D genome organization, they are absent in Arabidopsis. However, a few research groups have reported the presence of TAD-like structures in the plant kingdom.

Reduction in gene expression noise by targeted increase in accessibility at gene loci

Many eukaryotic genes are expressed in randomly initiated bursts that are punctuated by periods of quiescence. Here, we show that the intermittent access of the promoters to transcription factors through relatively impervious chromatin contributes to this "noisy" transcription. We tethered a nuclease-deficient Cas9 fused to a histone acetyl transferase at the promoters of two endogenous genes in HeLa cells. An assay for transposase-accessible chromatin using sequencing showed that the activity of the histone acetyl transferase altered the chromatin architecture locally without introducing global changes in the nucleus and rendered the targeted promoters constitutively accessible. We measured the gene expression variability from the gene loci by performing single-molecule fluorescence in situ hybridization against mature messenger RNAs (mRNAs) and by imaging nascent mRNA molecules present at active gene loci in single cells. Because of the increased accessibility of the promoter to transcription factors, the transcription from two genes became less noisy, even when the average levels of expression did not change. In addition to providing evidence for chromatin accessibility as a determinant of the noise in gene expression, our study offers a mechanism for controlling gene expression noise which is otherwise unavoidable.

Pathway dynamics can delineate the sources of transcriptional noise in gene expression

Single-cell expression profiling opens up new vistas on cellular processes. Extensive cell-to-cell variability at the transcriptomic and proteomic level has been one of the stand-out observations. Because most experimental analyses are destructive we only have access to snapshot data of cellular states. This loss of temporal information presents significant challenges for inferring dynamics, as well as causes of cell-to-cell variability. In particular, we typically cannot separate dynamic variability from within cells ('intrinsic noise') from variability across the population ('extrinsic noise'). Here, we make this non-identifiability mathematically precise, allowing us to identify new experimental set-ups that can assist in resolving this non-identifiability. We show that multiple generic reporters from the same biochemical pathways (e.g. mRNA and protein) can infer magnitudes of intrinsic and extrinsic transcriptional noise, identifying sources of heterogeneity. Stochastic simulations support our theory, and demonstrate that 'pathway-reporters' compare favourably to the well-known, but often difficult to implement, dual-reporter method.

RN7SK small nuclear RNA controls bidirectional transcription of highly expressed gene pairs in skin

Pausing of RNA polymerase II (Pol II) close to promoters is a common regulatory step in RNA synthesis, and is coordinated by a ribonucleoprotein complex scaffolded by the noncoding RNA RN7SK. The function of RN7SK-regulated gene transcription in adult tissue homoeostasis is currently unknown. Here, we deplete RN7SK during mouse and human epidermal stem cell differentiation. Unexpectedly, loss of this small nuclear RNA specifically reduces transcription of numerous cell cycle regulators leading to cell cycle exit and differentiation. Mechanistically, we show that RN7SK is required for efficient transcription of highly expressed gene pairs with bidirectional promoters, which in the epidermis co-regulated cell cycle and chromosome organization. The reduction in transcription involves impaired splicing and RNA decay, but occurs in the absence of chromatin remodelling at promoters and putative enhancers. Thus, RN7SK is directly required for efficient Pol II transcription of highly transcribed bidirectional gene pairs, and thereby exerts tissue-specific functions, such as maintaining a cycling cell population in the epidermis.

The noncoding RNA RN7SK regulates RNA polymerase II pausing and splicing. Here the authors deplete RN7SK in mouse and human during epidermal stem cell differentiation and reveal a novel role in orchestrating bidirectional transcription of highly expressed gene pairs.

Distinguishing between models of mammalian gene expression: telegraph-like models versus mechanistic models

Two-state models (telegraph-like models) have a successful history of predicting distributions of cellular and nascent mRNA numbers that can well fit experimental data. These models exclude key rate limiting steps, and hence it is unclear why they are able to accurately predict the number distributions. To answer this question, here we compare these models to a novel stochastic mechanistic model of transcription in mammalian cells that presents a unified description of transcriptional factor, polymerase and mature mRNA dynamics. We show that there is a large region of parameter space where the first, second and third moments of the distributions of the waiting times between two consecutively produced transcripts (nascent or mature) of two-state and mechanistic models exactly match. In this region: (i) one can uniquely express the two-state model parameters in terms of those of the mechanistic model, (ii) the models are practically indistinguishable by comparison of their transcript numbers distributions, and (iii) they are distinguishable from the shape of their waiting time distributions. Our results clarify the relationship between different gene expression models and identify a means to select between them from experimental data.

PRC1 drives Polycomb-mediated gene repression by controlling transcription initiation and burst frequency

The Polycomb repressive system plays a fundamental role in controlling gene expression during mammalian development. To achieve this, Polycomb repressive complexes 1 and 2 (PRC1 and PRC2) bind target genes and use histone modification-dependent feedback mechanisms to form Polycomb chromatin domains and repress transcription. The inter-relatedness of PRC1 and PRC2 activity at these sites has made it difficult to discover the specific components of Polycomb chromatin domains that drive gene repression and to understand mechanistically how this is achieved. Here, by exploiting rapid degron-based approaches and time-resolved genomics, we kinetically dissect Polycomb-mediated repression and discover that PRC1 functions independently of PRC2 to counteract RNA polymerase II binding and transcription initiation. Using single-cell gene expression analysis, we reveal that PRC1 acts uniformly within the cell population and that repression is achieved by controlling transcriptional burst frequency. These important new discoveries provide a mechanistic and conceptual framework for Polycomb-dependent transcriptional control.

The Core Promoter Is a Regulatory Hub for Developmental Gene Expression

The development of multicellular organisms and the uniqueness of each cell are achieved by distinct transcriptional programs. Multiple processes that regulate gene expression converge at the core promoter region, an 80 bp region that directs accurate transcription initiation by RNA polymerase II (Pol II). In recent years, it has become apparent that the core promoter region is not a passive DNA component, but rather an active regulatory module of transcriptional programs. Distinct core promoter compositions were demonstrated to result in different transcriptional outputs. In this mini-review, we focus on the role of the core promoter, particularly its downstream region, as the regulatory hub for developmental genes. The downstream core promoter element (DPE) was implicated in the control of evolutionarily conserved developmental gene regulatory networks (GRNs) governing body plan in both the anterior-posterior and dorsal-ventral axes. Notably, the composition of the basal transcription machinery is not universal, but rather promoter-dependent, highlighting the importance of specialized transcription complexes and their core promoter target sequences as key hubs that drive embryonic development, differentiation and morphogenesis across metazoan species. The extent of transcriptional activation by a specific enhancer is dependent on its compatibility with the relevant core promoter. The core promoter content also regulates transcription burst size. Overall, while for many years it was thought that the specificity of gene expression is primarily determined by enhancers, it is now clear that the core promoter region comprises an important regulatory module in the intricate networks of developmental gene expression.

Transcription factor binding kinetics and transcriptional bursting: What do we really know?

In eukaryotes, transcription is a discontinuous process with mRNA being generated in bursts, after the binding of transcription factors (TFs) to regulatory elements on the genome. Live-cell single-molecule microscopy has highlighted that transcriptional bursting can be controlled by tuning TF/DNA binding kinetics. Yet the timescales of these two processes seem disconnected with TF/DNA interactions typically lasting orders of magnitude shorter than transcriptional bursts. To test models that could reconcile these discrepancies, reliable measurements of TF binding kinetics are needed, also accounting for the current limitations in performing these single-molecule measurements at specific regulatory elements. Here, we review the recent studies linking TF binding kinetics to transcriptional bursting and outline some current and future challenges that need to be addressed to provide a microscopic description of transcriptional regulation kinetics.

RNA polymerase II clusters form in line with surface condensation on regulatory chromatin

It is essential for cells to control which genes are transcribed into RNA. In eukaryotes, two major control points are recruitment of RNA polymerase II (Pol II) into a paused state, and subsequent pause release toward transcription. Pol II recruitment and pause release occur in association with macromolecular clusters, which were proposed to be formed by a liquid-liquid phase separation mechanism. How such a phase separation mechanism relates to the interaction of Pol II with DNA during recruitment and transcription, however, remains poorly understood. Here, we use live and super-resolution microscopy in zebrafish embryos to reveal Pol II clusters with a large variety of shapes, which can be explained by a theoretical model in which regulatory chromatin regions provide surfaces for liquid-phase condensation at concentrations that are too low for canonical liquid-liquid phase separation. Model simulations and chemical perturbation experiments indicate that recruited Pol II contributes to the formation of these surface-associated condensates, whereas elongating Pol II is excluded from these condensates and thereby drives their unfolding.